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Peter Wang is focused on robotics and automation at the Department of Energy’s Manufacturing Demonstration Facility at ORNL, working on high-profile projects such as the MedUSA, a large-scale hybrid additive manufacturing machine.

Scientists at have experimentally demonstrated a novel cryogenic, or low temperature, memory cell circuit design based on coupled arrays of Josephson junctions, a technology that may be faster and more energy efficient than existing memory devices.

A select group gathered on the morning of Dec. 20 at the Department of Energy’s Oak Ridge National Laboratory for a symposium in honor of Liane B. Russell, the renowned ORNL mammalian geneticist who died in July.

Ancient Greeks imagined that everything in the natural world came from their goddess Physis; her name is the source of the word physics.

While Tsouris’ water research is diverse in scope, its fundamentals are based on basic science principles that remain largely unchanged, particularly in a mature field like chemical engineering.

In the shifting landscape of global manufacturing, American ingenuity is once again giving U.S companies an edge with radical productivity improvements as a result of advanced materials and robotic systems developed at the Department of Energy’s Manufacturing Demonstration Facility (MDF) at Oak Ridge National Laboratory.

Researchers at the Department of Energy’s Oak Ridge National Laboratory, Pacific Northwest National Laboratory and Washington State University teamed up to investigate the complex dynamics of low-water liquids that challenge nuclear waste processing at federal cleanup sites.

When Scott Smith looks at a machine tool, he thinks not about what the powerful equipment used to shape metal can do – he’s imagining what it could do with the right added parts and strategies. As ORNL’s leader for a newly formed group, Machining and Machine Tool Research, Smith will have the opportunity to do just that.

Using artificial neural networks designed to emulate the inner workings of the human brain, deep-learning algorithms deftly peruse and analyze large quantities of data. Applying this technique to science problems can help unearth historically elusive solutions.

Alex Roschli is no stranger to finding himself in unique situations. After all, the early career researcher in ORNL’s Manufacturing Systems Research group bears a last name that only 29 other people share in the United States, and he’s certain he’s the only Roschli (a moniker that hails from Switzerland) with the first name Alex.